Swarm Dashboard

Swarm Dashboard Skill

Real-time monitoring for AI agent swarms with a beautiful, auto-refreshing web UI.

Quick Start

from swarm_dashboard import launch_dashboard, update_agent_task_id

# Launch dashboard
url = launch_dashboard(
    swarm_name="My Project",
    swarm_dir="/workspace/my-project",
    agents={
        "agent-1": {"role": "Core Architect", "wave": 1, "mission": "Setup"},
        "agent-2": {"role": "Backend Dev", "wave": 2, "mission": "Build API"},
    }
)

# After launching each agent with Task tool, update task ID
update_agent_task_id(
    swarm_dir="/workspace/my-project",
    agent_id="agent-1",
    task_id="abc123"  # From Task tool response
)

Features

• Real-time Updates - Auto-refreshes every 2 seconds
• Smart Completion Detection - Auto-detects finished agents
• Capybara-Inspired UI - Natural color palette with light/dark themes
• Clickable Details - Live activity feed, tools used, files created
• Zero Dependencies - Pure Python stdlib

CLI Usage

# Start server
swarm-dashboard serve --port 8080 --swarm-dir /workspace

# Launch in background
swarm-dashboard launch --name "My Swarm" --dir /workspace

# Check status
swarm-dashboard status --dir /workspace

# Stop
swarm-dashboard stop --dir /workspace

Configuration

Environment variables:

• SWARM_DIR - Directory with agent folders
• TASK_DIR - Directory with task outputs
• DASHBOARD_PORT - Server port (default 8080)
• SWARM_NAME - Display name

API Endpoints